Uncensored AI Models: API Quickstart

Base URL & Authentication

Use the base URL https://api.uncensoredaimodels.com/v1 with your API key. Sign up on the Get API key page with just an email and password. The key is shown immediately after signup. No phone number or card is needed for the trial credit.

• Base URL: https://api.uncensoredaimodels.com/v1
• Auth: Bearer token in the Authorization header

Change the base_url in your SDK client to point to our endpoint. The model ID is always uncensored.

First Request

Send a standard chat completion request. The model is tuned to answer without content refusals for lawful adult use, though it blocks sexual content involving minors.

Copycurl https://api.uncensoredaimodels.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Write a blunt product review of a cheap VPN."}]
  }'

You can check available models via GET /v1/models. The response confirms the single uncensored model is available for your integration.

Python SDK Integration

Use the official OpenAI Python package. Configure the client with our base URL and your key. This works for any standard chat completion call.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.uncensoredaimodels.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Pass the message array with the model ID uncensored. The API supports standard parameters like temperature and max_tokens. No special SDK is required.

Node SDK Integration

Initialize the OpenAI Node client with our custom base URL. This allows you to use familiar JavaScript patterns for API calls.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.uncensoredaimodels.com/v1", apiKey: process.env.API_KEY });

const resp = await client.chat.completions.create({
  model: "uncensored",
  messages: [{ role: "user", content: "Draft a villain monologue for my game." }],
});
console.log(resp.choices[0].message.content);

Set the apiKey and baseURL. Call chat.completions.create with the model set to uncensored. The response format matches the standard OpenAI schema.

Streaming Responses

Enable streaming by setting stream: true. The API returns Server-Sent Events (SSE). Parse the delta chunks to update your UI in real time.

Copystream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Each chunk contains partial text. Handle the done event to finalize the response. This reduces perceived latency for long outputs.

Limits, Errors & Context

Your request body must be under 8 MB. You are limited to 300 requests per minute per key. If you exceed this, you receive a 429 error. Use 401 for invalid keys and 402 if prepaid credit is exhausted. The context window is 100,000 tokens total. Prompts are not used for training. Regenerate your key anytime from the dashboard.